Abstract
Video sequences captured over a long range through the turbulent atmosphere contain some degree of
atmospheric turbulence degradation (ATD). Stabilization of the geometric distortions present in video sequences containing
ATD and containing objects undergoing real motion is a challenging task. This is due to the difficulty of
discriminating what visible motion is real motion and what is caused by ATD warping. Due to this, most stabilization
techniques applied to ATD sequences distort real motion in the sequence. In this study we propose a new method
to classify foreground regions in ATD video sequences. This classification is used to stabilize the background of the
scene while preserving objects undergoing real motion by compositing them back into the sequence. A hand annotated
dataset of three ATD sequences is produced with which the performance of this approach can be quantitatively
measured and compared against the current state-of-the-art.